1. Field of the Invention
The invention generally relates to image/video processing and, more specifically, relates to image/video compression, transmission, and decompression while minimizing degradation.
2. Description of Related Art
In recent years, the market for visual communications has exploded market due to advances in image/video compression and to the maturity of digital signal processors (DSP) and Very Large Scale Integrated (VLSI) technologies. Hereafter, xe2x80x9cimagexe2x80x9d will refer to still frame images and video. Image transmission/compression standards such as those of the Motion Photographic Expert Group (MPEG), the Motion Joint Photographic Expert Group (Motion JPEG) and the International Telegraph and Telephone Consultative Committee (CCITT) H.261, and H.263 were ratified for the applications of digital video disc, digital satellite TV, digital video phone, video/teleconferencing, and related telecommunication systems. However, these standards do not adequately meet the need for the processing of image signals in real-time at a low transmission rates (including, for example, 28.8 KB per second) with acceptable image quality. Currently, technological obstacles exist in obtaining high levels of image compression with high fidelity utilizing conventional and practiced image processing techniques. For example, systems implementing the above standards fail to adequately handle high volumes of data with acceptable image data loss. Therefore, seeking an image enhancement system and method is as important as seeking a high fidelity image compression system and method.
Since the development of digital signal processes in the early 1980""s, the wavelet transform (WT) has been widely embraced by the scientific community, displacing the Fourier transform for mathematical analysis. In recent years, a digital form of the wavelet transform called the Discrete Wavelet Transform (DWT) has become a conventional tool for image processing and image compression. The DWT is a lossless transform, which is used to form an orthonormal basis of some and a dilated master function over a range of, shift and dilation parameters. The principle behind the wavelet transform is to hierarchically decompose the input signals into a series of successively lower resolution reference signals and their associated detail signals. At each level, the reference signals and detailed signals contain the information needed for reconstruction back to the next higher resolution level. The Inverse Discrete Wavelet Transform (IDWT) is the inverse function of the DWT. The one-dimensional DWT (1D DWT) processing can be described in terms of a filter bank, wherein an input signal is analyzed in both low and high frequency bands. A separable two-dimensional DWT (2D DWT) process is an extension of the 1D DWT. Specifically, in the 2D DWT process, separable filter banks are applied first horizontally and then vertically. Application of a filter bank comprising two filters, first horizontally then vertically, gives rise to an analysis in four frequency bands: horizontal lowxe2x80x94vertical low; horizontal lowxe2x80x94vertical high; horizontal highxe2x80x94vertical low; and horizontal highxe2x80x94vertical high. Each resulting band is encoded according to its own statistics for transmission from a coding station to a receiving station. However, constraints exist on how filters can be designed and/or selected, including the need to output perfect reconstructed versions of initially input data, the finite-length of the filters, and a regularity requirement that the iterated low pass filters involve convergence to continuous functions. Further, the implementation of the DWT per se in line with the above constraints for image processing and de-processing fails to meet the desired throughput over low bandwidth communications channels.
The present invention relates to an image/video enhancement system, method, and medium. Through the use of a preprocessor and a postprocessor, an image may be placed in a better condition for transmission/compression without significant image loss. In one embodiment, the preprocessor formats the received image to a predefined size, enhances the edges of elements within the image, and eliminates useless image information. The postprocessor restores the received image to a high-quality resultant image.